Include references and avoid plagiarism when answering this, it is a graduate research NON-EXPERIMENTAL STUDY paper: Review the following attached articles that have been provided as example studies
Chinwe Eluagu 1 Association between body mass index, hypertension, and diabetes S tudy objectives Engagement of the young adults in a physical exercise program will have numerous objectives, firstly is to understand the relationship between obesity and physical exercise. If the subjects' overall weight reduces due to exercise, then t here will be some significant changes . ( Tsimihodimos et al. 2018 ). The second objective is a comparison between the body mass index of people that participate and others th at do not participate in physical exercise to understand the changes that physical exercise has on people. The third objective is observing the long - term impacts of physical activity on individ uals since, although the process takes longer, most scientists acknowledge that it is the most significan t. Background Over the past few years, a gradual increase in the body mass index among the young adults between 25 and 40 years old has increased significantly due to a lack of physical exercise and nutrition patterns. An example is , due to the economic nature of our society, people take their vehicles t o work and remain seated for long hours at work . This affects the quality of physical exercise; young adults are also taking sugary and fast foods associated with a huge number of calories, thus increasing their overall weight. For this study, we will seek to unde rstand the importance of physical exercising among the young adults in reducing the body mass index, thus reducing cases of hypertension and diabetes. This will create a long - term method of solving the obesity issue since if a culture of physical exercising is i ntroduced for young adults, it will be adhered to throughout their adulthood. 2 Research question and hypothesis How does physical exercise intervention among obese young adults help reduce body mass index compared to those not undertaking the program for six months? The alternative hypothesis is after engaging in phys ical exercises for six months, the young adult ’ s overall body mass index will reduce significantly tha n those who do not participate in the physical exercise programs. While the null hypothesis is there will be no difference in the body mass index for young adults who undergo the exercise program for six months. The hypothesis will be testable since the young adults will be weighed before engaging in the research process with the ir weight recorded at every interval . B y every four weeks of physical exercising, the subject will be cons idered to track the progress. The physical exercise will be mild, including walking to work instead of driving and visiting the gym for one hour daily. Patient eligibility The patients involved in this study should be between 25 and 40 years old, and they should consent to the study by agreeing to regular exercise and programs r elating to reducing weight. They should have flexible work schedules since the program involves one hour of gym attendance per day. The data to be collected from the patient will include their height and weight after four weeks to observe and no te the differences. ( Pribis et al. 2010). The variables The physical exercise intervention will be the independent variable that can be changed and manipulated by the author to reach the required results. An example is , the control group will 3 not engage in physical exercising while the experimental group will engage in a physical exercise program, thus noting the differences between the groups . While the body mass index wi ll be the dependent variable which will change upon engagement in continuous physical exercising, evaluation of participants will occur monthly (four weeks) to note the changes and effectiveness of the study. S tudy design The randomized control trial will be the most effective in this study since the participants in the intervention group will be regularly involved in physical exercise programs, and changes will be noted to ensure there is significance while in the control group. This will be the most effective method since the differences and changes in weight between the two groups will be observed and recorded gradually to ensure there are effects on the experimen tal group. Recruitment Numerous methods would be used to recruit participants; however, electronic health records will be the most significant since data is already available regarding the patient's BMI.Therefore, those eligible will receive messages but consent to the study. Before consent, everyone will have to understand the risks and issues relating to participation, such as discomfort when one must regularly attend the gym and walk instead of driving for physical fitness. Outcomes, intervention, an d covariates With t he experimental group, there would be a significant reduction of their BMI with consistent and continuous engagement in physical exercises. As participants continued to engage, their overall health was better. However, for the control group, the results were often 4 similar since the results were no change in weight. There were other covariates in the study; nutrition was highly significant since engagement in an excellent physical exercising program was not successful without proper diets. Gender affected the responses of d ifferent genders to exercise programs; for example, the males were more proactive in the programs than the females.
( Wang et al. 2004). E - protocol tool use & Reflection The electronic health records informatics tool was highly significant since, in our healthcare facility, there are different records and charts a bout patients; therefore, locating participants was not difficult. It only required seeking authorization from the management and sending emails and messages to patients for consent. Most patients were will ing to participate since they were aware of physical exercise and nutrition impacts on their healthcare. The method was more significant than physically locating patients and participants, which would be difficult considering the need to protect privacy. There are different features assessed; firstly, there are patient demographics, including their insurance, age, names, contacts, and gender. Since, in the study, young adults between 25 and 40 years were required, we only selected such participants. We also neede d to balance the two genders; therefore, while sending messages, the two were informed. ( Evans, 2016). We also focused on the clinical notes feature of the electronic health records; for example, in every encounter with physicians, there are records of phy sical examination results, treatments etc. therefore, the notes helped ensure the involved patients did not have underlining conditions that would jeopardize their wellbeing. 5 Other essential features are not provided, such as the patient's occupation and nutrition patterns, which would have been successful in the study. An example like patient flexibility was required for the intervention group to ensure they had adequate time for physical exercising and walking to work. Additionally, the nutrition behavior wa s significant in the project's success. ( Kohli & Tan 2016). An example was, patients taking healthy food like carbs and fruits regularly had a higher possibility of excellent results. The significant difficulty was patient privacy concerns since when patients give their information to the healthcare facility, they expect it to be protected from third - party access. Therefore, most respondents wondered how we accessed the information; however, after explaining that we were part of the healthcare facility researc h and development team, they were willing to participate . Therefore, I would prefer to use the electronic health records informatics tools other than physically looking for participants, which would take a longer duration and mos t would resist engagement. 6 References Evans, R. S. (2016). Electronic health records: then, now, and in the future. Yearbook of medical informatics , 25 (S 01), S48 - S61. https://www.thieme - connect.com/products/ejournals/html/10.15265/IYS - 2016 - s006 Garg, H., Batra, N., Singh, G., & Mujral, A. (2022). Hypertension and Diabetes Mellitus: Coprediction and Time Trajectories. Indian Journal of Public Health Research & De velopment , 13 (3), 102 - 106. https://revistaamplamente.com/index.php/ijphrd/article/download/18178/15904 Kohli, R., & Tan, S. S. L. (2016). Electronic Health Records . Mis Quarterly , 40 (3), 553 - 574. https://www.jstor. org/stable/pdf/26629027.pdf?casa_token=_0xv4Vh5lowAAAAA:HQG biEY3haJ2rq9IlSHMh4Nv - Ww0aH9CcwNEZ2CNRSIjTJs70jNTqfKc2b8njo5wpMurup9I9OWESE6ybRRkgOxF0 O6MenFimo0ToWrA9e9aptoDH88 Pribis, P., Burtnack, C. A., McKenzie, S. O., & Thayer, J. (2010). Trends in body fat, body mass index and physical fitness among male and female college students. Nutrients , 2 (10), 1075 - 1085. https://www.mdpi.com/2072 - 6643/2/10/1075/pdf Tsimihodimos, V., Gonzalez - Villalpando, C., Meigs, J. B., & Ferrannini, E. (2018). Hypertension and diabetes mellitus: coprediction and time trajectories. Hypertension , 71 (3), 422 - 428. https://www.ahajournals. org/doi/full/10.1161/HYPERTENSIONAHA.117.10546 7 Wang, F., McDonald, T., Champagne, L. J., & Edington, D. W. (2004). Relationship of body mass index and physical activity to health care costs among employees. Journal of Occupational and Environmental Medici ne , 428 - 436. https://www.jstor.org/stable/pdf/44996 617.pdf?casa_token=rj2 - cn_R - BgAAAAA:yd0m4uaVZ1kJtQUhbY6AXC2xjx5z6dBnMLRDwgcsfn0IfUaFBDp2vYw WbahtOCnO62nE8N4p6k5yIPW_KYwK6lfx6KjxHEMIdoXfkCkHYU_f - UgMFEs
